Using multi-perspective methodologies to study users' interactions with the prototype front end of a guideline-based decision support system for diabetic foot care

PURPOSE Clinical practice guidelines are important instruments for improving the quality of care; in paper form, however, they are not used as effectively as possible. In order to develop a guideline-based decision support system (DSS) prototype to help clinicians deal with diabetic patients' foot problems, we drew on methodologies from qualitative research, cognitive science, and information systems. This multi-perspective approach was intended to facilitate user-centered design and evaluation. METHODS We employed field observations, structured interviews, and document analyses to collect and analyze users' workflow patterns, decision support goals, and preferences regarding interactions with a DSS. Next, we aligned their requirements with sequence diagrams and followed Nielsen's heuristics to develop a DSS prototype. We then performed think-aloud analyses and used the technology acceptance model to direct our evaluation of users' perceptions of the prototype. RESULTS Users had a positive response to the DSS prototype in terms of its clarity of design and ease of use. They expressed a high intention of using the system in the future. CONCLUSION Applying multi-perspective methodologies is an effective way to study and design user interactions with the front end of a guideline-based DSS.

[1]  Austin Henderson,et al.  Interaction design: beyond human-computer interaction , 2002, UBIQ.

[2]  M. Peleg,et al.  Adaptation of Practice Guidelines for Clinical Decision Support : A Case Study of Diabetic Foot Care , 2006 .

[3]  Tia Gao,et al.  Iterative User-Centered Design of a Next Generation Patient Monitoring System for Emergency Medical Response , 2006, AMIA.

[4]  John Mylopoulos,et al.  Towards requirements-driven information systems engineering: the Tropos project , 2002, Inf. Syst..

[5]  Omolola Ogunyemi,et al.  GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines , 2004, J. Biomed. Informatics.

[6]  Vimla L. Patel,et al.  Designing Human-Centered Distributed Information Systems , 2002, IEEE Intell. Syst..

[7]  M. Deering,et al.  User-Centered Research on Breast Cancer Patient Needs and Preferences of an Internet-Based Clinical Trial Matching System , 2007, Journal of medical Internet research.

[8]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[9]  Todd R. Johnson,et al.  A user-centered framework for redesigning health care interfaces , 2005, J. Biomed. Informatics.

[10]  Omolola Ogunyemi,et al.  Design and implementation of the GLIF3 guideline execution engine , 2004, J. Biomed. Informatics.

[11]  Vimla L. Patel,et al.  Cognitive and usability engineering methods for the evaluation of clinical information systems , 2004, J. Biomed. Informatics.

[12]  M. Lindell,et al.  A Revised Index of Interrater Agreement for Multi-Item Ratings of a Single Target , 1999 .

[13]  Richard Heeks,et al.  Health information systems: Failure, success and improvisation , 2006, Int. J. Medical Informatics.

[14]  Joey F. George,et al.  Modern Systems Analysis and Design , 1996 .

[15]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[16]  Annemarie A. Edwards,et al.  Diabetic foot disorders: A clinical practice guideline , 2000 .

[17]  L. Hayden,et al.  Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality , 2011 .

[18]  D. Armstrong,et al.  A Supplement to : Foot & Ankle Surgery , 2006 .

[19]  Thomas Wetter,et al.  Lessons learnt from bringing knowledge-based decision support into routine use , 2002, Artif. Intell. Medicine.

[20]  Sri Hastuti Kurniawan,et al.  Review of Interaction design , 2003 .

[21]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[22]  William DuMouchel,et al.  A meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting. , 1996, Journal of the American Medical Informatics Association : JAMIA.